【摘要】 针对死区等非线性特征对光伏并网逆变器电能质量的影响,该文借助数据驱动的补偿方法与传统控制相结合,研究一种并网逆变器动静态特征优化方法。首先利用重复控制器作为数据在线训练的依据,从机理上阐明数据来源和数据的有效性;其次利用近似线性回归方法获得数据模型,降低了数据驱动方法对存储空间的依赖度,保障了必要的补偿带宽,并解决了数据应用的可实现性问题;再将该模型作用于传统低阶控制器的补偿回路,使系统在具备足够稳定裕度的前提下实现良好的控制精度。数据相关性分析以及实验结果证明了该补偿方法具有可实现性和有效性。更多还原

【Abstract】 Addressing the impact of nonlinear characteristics such as dead-zones on the power quality of photovoltaic grid-connected inverters, this paper combines data-driven compensation methods with traditional control to investigate a dynamic and static characteristic optimization approach for grid-connected inverters. Firstly, a repetitive controller is utilized as the basis for online data training, elucidating the mechanism and validity of the data source. Secondly, an approximate linear regression method is employed to obtain a data model, reducing the dependence on storage space for data-driven methods, ensuring necessary compensation bandwidth, and solving the feasibility of data application. This model is then applied to the compensation loop of a traditional low-order controller, enabling the system to achieve precise control with sufficient stability margin. Data correlation analysis and experimental results demonstrate the feasibility and effectiveness of this compensation method.更多还原